Ignite Creation Date:
2025-12-25 @ 3:29 AM
Ignite Modification Date:
2025-12-26 @ 2:10 AM
Study NCT ID:
NCT05819905
Status:
UNKNOWN
Last Update Posted:
2023-04-19
First Post:
2023-03-17
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Radiomics for prEdiction of lunG cAncer biologY
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002289', 'term': 'Carcinoma, Non-Small-Cell Lung'}], 'ancestors': [{'id': 'D002283', 'term': 'Carcinoma, Bronchogenic'}, {'id': 'D001984', 'term': 'Bronchial Neoplasms'}, {'id': 'D008175', 'term': 'Lung Neoplasms'}, {'id': 'D012142', 'term': 'Respiratory Tract Neoplasms'}, {'id': 'D013899', 'term': 'Thoracic Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D000072078', 'term': 'Positron Emission Tomography Computed Tomography'}], 'ancestors': [{'id': 'D049268', 'term': 'Positron-Emission Tomography'}, {'id': 'D014055', 'term': 'Tomography, Emission-Computed'}, {'id': 'D007090', 'term': 'Image Interpretation, Computer-Assisted'}, {'id': 'D003952', 'term': 'Diagnostic Imaging'}, {'id': 'D019937', 'term': 'Diagnostic Techniques and Procedures'}, {'id': 'D003933', 'term': 'Diagnosis'}, {'id': 'D014057', 'term': 'Tomography, X-Ray Computed'}, {'id': 'D064847', 'term': 'Multimodal Imaging'}, {'id': 'D011856', 'term': 'Radiographic Image Enhancement'}, {'id': 'D007089', 'term': 'Image Enhancement'}, {'id': 'D010781', 'term': 'Photography'}, {'id': 'D011859', 'term': 'Radiography'}, {'id': 'D014056', 'term': 'Tomography, X-Ray'}, {'id': 'D011877', 'term': 'Radionuclide Imaging'}, {'id': 'D014054', 'term': 'Tomography'}, {'id': 'D003947', 'term': 'Diagnostic Techniques, Radioisotope'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 600}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2023-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-04', 'completionDateStruct': {'date': '2024-01-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-04-05', 'studyFirstSubmitDate': '2023-03-17', 'studyFirstSubmitQcDate': '2023-04-05', 'lastUpdatePostDateStruct': {'date': '2023-04-19', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-04-19', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-01-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'prediction of PDL1 expression', 'timeFrame': '1 month', 'description': 'Evaluation of the performances of PET/CT derived radiomics to predict PDL1 expression \\>1% (PDL1 : Programmed death-ligand 1 as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.'}, {'measure': 'prediction of EGFR genomic alteration', 'timeFrame': '1 month', 'description': 'Evaluation of the performances of PET/CT derived radiomics to predict the presence of EGFR mutation (EGFR: epidermal growth factor receptor, presence /or not of EGFR alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.'}], 'secondaryOutcomes': [{'measure': 'Prediction of KRAS alteration', 'timeFrame': '1 month', 'description': 'Evaluation of the performances of PET/CT derived radiomics to predict the presence of KRAS mutation (KRAS : Kirsten rat sarcoma viral oncogene : presence/or not of KRAS alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.'}, {'measure': 'Prediction of BRAF mutation', 'timeFrame': '1 month', 'description': 'Evaluation of the performances of PET/CT derived radiomics to predict the presence of BRAF mutation (BRAF : raf murine sarcoma viral oncogene homolog B, presence/or not of BRAF mutation as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.'}, {'measure': 'Prediction of ALK/ROS translocation', 'timeFrame': '1 month', 'description': 'Evaluation of the performances of PET/CT derived radiomics to predict the presence of ALK/ROS translocation (ALK : anaplastic lymphoma receptor tyrosine kinase, ROS : c-ROS protooncogene 1; presence /or not of ALK and ROS alteration as previously determined on routine tumoral biopsy): area under the receiver operating characteristics curve (AUC), accuracy, sensitivity and specificity.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Non Small Cell Lung Cancer', 'PET/CT', 'PD-L1', 'Gene Mutation-Related Cancer']}, 'descriptionModule': {'briefSummary': 'Therapeutic progress for subgroups of Non Small Cell Lung Cancer can largely be attributed to the accumulation of molecular knowledge and the development of new drugs that specifically target molecular abnormalities. An understanding of the immune landscape of tumors, including immune-evasion strategies, has also led to breakthrough therapeutic advances.These new options require prior treatment tumoral sampling to identify patients who have neoplasms with specific genomic aberrations or favorable immune environment. Medical imaging and radiomic approach may provides surrogate markers non invasively.The objective of the present retrospective study is to build and validate a predictive model of common molecular alterations and PD-L1 expression in NSCLC using pre treatment PET/CT derived radiomics.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Histologically proven NSCLC with molecular biology analysis and initial staging PET/CT', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Histologically proven NSCLCC\n* pre treatment 18F FDG PET/CT\n* available molecular biology and histology results\n\nExclusion Criteria:\n\n* non available PET/CT images'}, 'identificationModule': {'nctId': 'NCT05819905', 'briefTitle': 'Radiomics for prEdiction of lunG cAncer biologY', 'organization': {'class': 'OTHER', 'fullName': 'Poitiers University Hospital'}, 'officialTitle': 'Prediction of Lung Cancer Characteristics Using PET/CT Radiomics', 'orgStudyIdInfo': {'id': 'REGAL'}}, 'armsInterventionsModule': {'interventions': [{'name': 'PET/CT', 'type': 'DIAGNOSTIC_TEST', 'description': 'Pre treatment staging 18F-FDG PET/CT'}]}, 'contactsLocationsModule': {'locations': [{'zip': '86000', 'city': 'Poitiers', 'country': 'France', 'facility': 'CHU Poitiers', 'geoPoint': {'lat': 46.58261, 'lon': 0.34348}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Poitiers University Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}